Jobs at Dotmatics

Build and maintain automated and manual tests for a LUMA software module using Cypress, TypeScript, Cucumber, and Playwright. Own quality activities including test planning, functional and integration testing, defect investigation, JIRA reporting, API coverage, and CI pipeline reliability. Collaborate with developers, scientists, and DevOps engineers while contributing to release readiness and expanding technical expertise in scientific software testing.

The Product Business Analyst will bridge Product and Engineering within Agile Scrum teams, gathering and translating business requirements into epics, user stories, acceptance criteria, process flows, and functional documentation. Responsibilities include backlog refinement, stakeholder collaboration, UAT, product analytics, workflow analysis, risk mitigation, Agile ceremonies, and supporting wireframes and prototypes. The role requires extensive SaaS business analysis experience and close collaboration with Product, Engineering, QA, UX, and scientific stakeholders.

Build, operate, and improve secure, scalable AWS infrastructure for the ELN Platform. Responsibilities include infrastructure-as-code, automation, observability, monitoring, incident response, cloud security, reliability improvements, troubleshooting, peer code reviews, and collaboration with engineering, security, and DevOps teams.

Leads Dotmatics’ EMEA sales strategy for Luma and related scientific software solutions. Manages and develops regional account executives and sales representatives, drives territory and named-account planning, builds enterprise pipeline, supports complex multinational negotiations, and closes high-value SaaS deals. The role sells across R&D, tech transfer, and production environments while engaging scientific, operational, IT, and executive stakeholders. It also coordinates with Siemens business units, systems integrators, technology partners, marketing, product, and customer success teams.

Lead Dotmatics’ AI governance program by developing frameworks, risk tiering, use-case registries, policies, controls, and reporting aligned with regulations and standards. Coordinate the AI Governance Council and Siemens consortium, assess AI risks across product and business functions, embed controls into the SDLC, respond to customer due diligence, and deliver training. The role requires executive communication, cross-functional influence, technical understanding of AI/ML systems, and extensive information security, technology risk, compliance, and regulated-industry experience.